The European honey bee, Apis mellifera, is an important pollinator of horticultural and agricultural field crops, providing ≈ 90% of all commercial pollination services (Genersch et al. 2010). The recent rise in colony loss due to Colony Collapse Disorder (CCD) has been a source of concern for both beekeepers and the apiculture industry. One of the factors implicated in CCD is infestation by the ectoparasitic mite, Varroa destructor. Initial efforts to control the mite relied heavily on regular application of miticides without regard to actual mite infestation levels. This approach has led to problems of resistance in the mite and contamination of the hive and hive-products. Because it is unlikely that miticides will be removed as an option for mite management, a precision mite management (PMM) approach using information on the spatiotemporal distribution of the mite to improve sampling and treatments is seen as a viable option, particularly with respect to treatment costs and impacts on the environment. The primary objective of this study was to develop an understanding of the spatiotemporal distribution of the Varroa mite and bee brood within hives for the purpose of developing a PMM approach for the mite. Varroa mite populations were sampled from May to June, 2012 and February to October, 2013. Sampling was conducted with three commonly used sampling methods: soapy water roll (SWR), brood uncapping, and a modified sticky board; brood uncapping, however, was discontinued during the study due to hive the labor cost and harmful effects of this method to the hives. Similar trends in mite population levels were observed using the soapy water roll and sticky board sampling methods. Spearman's nonparametric analysis showed that there was a significant correlation (ρ = 0.47, P<0.001) in mite population levels for the soapy water roll and sticky board methods for sampling conducted from February to September, 2013 (the SWR method was not used in October). This was despite the fact that there was no significant correlation (ρ= -0.03, P = 0.8548) between the two sampling methods during the spring sampling period from February to April, 2013. The observed lack of correlation between the two sampling methods in early spring was likely due to the low population of brood in the hive, which caused the majority of the mites to remain on adult bees. Mites per 100 adult bees, therefore, appear to reflect mite population levels within the hive more closely than mite fall on sticky borad during the February to April sampling period. This suggests that the soapy water roll method is a better method for estimating mite population levels within the hive in the early spring compared with the sticky board method. Geospatial analyses of the distributions of mite fall on the sticky boards were conducted using geostatistics and Spatial Analysis by Distance IndicEs (SADIE). Both analyses showed that mite fall on the sticky board was generally aggregated and the aggregation increased with mite population levels. The average range of the variogram from geostatistical analysis was estimated at 4 sticky board cells; this range value was increased to 5 cells and was used to develop a systematic outside-range sampling protocol for mites on a sticky board. The results showed that the accuracy of the systematic outside-range sampling compared well with that of the traditional sticky board counting method in estimating total mite fall, but required only 60% of the effort (i.e., counting 63 instead of 105 cells). SADIE analysis showed that there is an overall association between the distribution of mite fall on a sticky board and the distribution of brood within a hive. A greater degree of correspondence was also observed in the association of drone and mite distributions during May to June; greater correspondence in worker brood and mite associations was observed in August and September. These differences may be due to relative amounts of the two types of brood present within the hive. A test of the efficacy of precision application of Varroa mite treatment based on the association between drone brood and mite fall resulted in a significantly greater reduction in mite levels on the sticky board using a traditional miticide treatment method compared with the control and precision treatments (𝜒2 =362.571; df = 2; P <0.0001); mite population levels with the precision method, however, were significantly reduced compared with the control. / Master of Science in Life Sciences

Made available in DSpace on 2015-04-13T12:17:43Z (GMT). No. of bitstreams: 1 Daniel_Ferreira.pdf: 1066470 bytes, checksum: 9923303dec16eec4c3bdffb317754755 (MD5) Previous issue date: 2012-08-13 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Model Digital Logging (Modeflora) technology that uses computer resources and highprecision equipment in tropical forest management, developed by Embrapa Acre (Rio Branco) and Embrapa Florestas (Colombo / PR), al.ows an accurate mapping of the area management, taking into account aspects of the reality of the forest. Since 2007 the technology is used by several companies timber in Acre in implementing their management plans. This work was validated utlização this methodology in the pre exploratory modeled hydrography and collecting the true coordinates of the trees in a forest management company owned by Precious Wooods Amazon, located in the city of Silves, Amazonas - Brazil. We obtained a map of hydrography of the study area and a database compared to the amount of trees by Modeflora method and the method practiced by the company. The Modeflora method is effective and easy to use. / O Modelo Digital de Exploração Florestal (Modeflora), tecnologia que utiliza recursos de informática e equipamentos de alta precisão no manejo de florestas tropicais, desenvolvido pela Embrapa Acre (Rio Branco) e Embrapa Florestas (Colombo/PR), permite um mapeamento rigoroso da área de manejo, levando em consideração aspectos da realidade da floresta. Desde 2007 a tecnologia é utilizada por diversas empresas do setor madeireiro acreano na execução de seus planos de manejo. Neste trabalho foi validado a utlização desta metodologia na fase pré-exploratória, modelando a hidrografia e coletando as coordenadas verdadeiras das árvores, em uma área de manejo florestal pertencente a empresa Precious Wooods Amazon, localizada no município de Silves, Amazonas Brasil. Foram obtidos mapa de hidrografia da região de estudo e um banco de dados comparado a quantidade de árvores inventarias pelo método Modeflora e pelo método praticado pela empresa. O método Modeflora se mostrou eficaz e de fácil utilização.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第22077号 / 農博第2369号 / 新制||農||1072(附属図書館) / 学位論文||R1||N5231(農学部図書室) / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 近藤 直, 教授 清水 浩, 教授 飯田 訓久 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM